This template has been produced using the posterdown package. It generates a standard conference-style poster layout.
A common problem in clinical research is messed up data1. It can lead to bias or nonsensical results. Appropriate statistical analysis can result in superb findings in such cases, with the right assumptions.
The syntax in this poster template and the posterdown package uses the same workflow approach as the R Markdown you know and love.
You can even use the bibliography the same way: Our data were taken from a cluster-randomised trial 2, available from the Irish Social Science Data Archive.
Usually you want to have a nice table displaying some important results that you have calculated. In posterdown this is as easy as using the kable table formatting you are probably use to as per typical R Markdown formatting.
You can reference tables like so: Table 1. Some basic summaries of the dataset are below:
| Sepal.Length | Sepal.Width | Petal.Length | Petal.Width |
|---|---|---|---|
| 5.1 | 3.5 | 1.4 | 0.2 |
| 4.9 | 3.0 | 1.4 | 0.2 |
| 4.7 | 3.2 | 1.3 | 0.2 |
| 4.6 | 3.1 | 1.5 | 0.2 |
| 5.0 | 3.6 | 1.4 | 0.2 |
| 5.4 | 3.9 | 1.7 | 0.4 |
| 4.6 | 3.4 | 1.4 | 0.3 |
| 5.0 | 3.4 | 1.5 | 0.2 |
| 4.4 | 2.9 | 1.4 | 0.2 |
| 4.9 | 3.1 | 1.5 | 0.1 |
Figure 1, and Figure 2 below show the patterns in our dataset. Make sure that all the details in your plots will be legible when printed (legend text, axis text, and any labels)
Figure 1: Great figure!
Figure 2: Amazing, right?!
You can even make your plots interactive for the HTML version of the poster. You can use the HTML poster for the presentation session, and the PDF poster will be printed - so be sure the static version looks okay.
Figure 3: Amazing, right?!
We plan to conduct further analysis using:
We will use the plasticanalysis package for this.
The code and datasets for this project can be viewed at our GitHub repository here: https://github.com/